The coding of video signals corresponding to the image coding standards H.261, H.263, MPEG1 and MPEG2 is based on a block-oriented discrete cosine transformation (DCT). In general, these methods use the principle of block-based image coding.
Another approach to image coding is what is called the principle of object-based image coding. In object-based image coding, a segmenting of the image documents takes place corresponding to the objects present in the scene, and a separate coding of these objects takes place.
FIG. 2 shows a general representation of an arrangement for image coding and image decoding.
FIG. 2 shows a camera K with which images are exposed. The camera K can for example be an arbitrary analog camera K that records images of a scene and either digitizes the images in the camera K or also transmits them in analog fashion to a first computer R1, in which then either the digitized images B are processed or the analog images are converted into digitized images B and the digitized images B are processed.
The camera K can also be a digital camera K with which digitized images B are recorded directly and are supplied to the first computer R1 for further processing.
The first computer R1 can also be fashioned as a separate arrangement with which the method steps specified below can be executed, for example as a separate computer card that is installed in a computer.
The first computer R1 comprises a processor unit P with which the method steps, specified below, of the image coding or of the image decoding can be executed. The processor unit P is coupled, for example via a bus BU, with a memory SP in which the image data are stored.
In general, the methods specified below can be realized both in software and in hardware, or also partly in software and partly in hardware.
After the image coding has taken place in the first computer R1, and after transmission of the compressed image data, via a transmission medium UW, to a second computer R2, the image decoding is carried out in the second computer R2.
The second computer R2 can have the same design as the first computer R1, i.e. the memory SP that is coupled with the processor unit P via the bus BU.
In FIG. 3, a possible arrangement, in the form of a schematic switching diagram for image coding or, respectively, for image decoding, is shown in detailed form, which arrangement can be used in the context of the block-based image coding and partly, as explained below, in the context of the object-based image coding.
In block-based image coding methods, a digitized image B is partitioned into, standardly, square blocks of size 8xc3x978 image points BP or 16xc3x9716 image points BP, and is supplied to the arrangement for image coding.
Coding information, e.g. brightness information (luminance values) or color information (chrominance values), is standardly allocated unambiguously to an image point.
In block-based image coding methods, distinctions are made between different image coding modes.
In what is called intra-image coding mode, the overall image is respectively coded with the overall coding information allocated to the image points of the image and is transmitted (I-image).
In what is called inter-image coding mode, only the difference image information of two chronologically successive images is coded and transmitted (P-image, B-image).
Two switching units SE are provided for the changeover between the intra-image coding mode and the inter-image coding mode. For the execution of the inter-image coding mode, a subtraction unit S is provided in which the difference of the image information of two successive images B is formed. The overall image coding is controlled via an image coding control unit ST. The image blocks BB or, respectively, difference image blocks BB to be coded are respectively supplied to a transformation coding unit DCT, in which a transformation coding, for example discrete cosine transformation (DCT), is applied to the coding information allocated to the image points.
In general, however, any transformation coding, e.g. a discrete sine transformation or also a discrete Fourier transformation, can be executed.
The spectral coefficients formed by the transformation coding are quantized in a quantization unit Q and are supplied to an image coding multiplexer (not shown), e.g. for channel coding and/or for entropy coding. In an internal reconstruction loop, the quantized spectral coefficients are inversely quantized in an inverse quantization unit IQ and are subjected to an inverse transformation coding in an inverse transformation coding unit IDCT.
In addition, in the case of inter-image coding, image information of the respective chronologically preceding image is added in an addition unit AE. The images reconstructed in this way are stored in an image memory SP. For simplicity of representation, in the image memory SP a unit for motion compensation MC is shown symbolically.
In addition, a loop filter (LF) is provided that is connected with the memory SP and with the subtraction unit S.
In addition to the image data to be transmitted, a mode flag p is supplied to the image coding multiplexer, which flag indicates whether an intra- or an inter-image coding was executed.
In addition, quantization indices q for the spectral coefficients are supplied to the image coding multiplexer.
A motion vector v is also respectively allocated to an image block and/or to a macro block that contains e.g. 4 image blocks, and is supplied to the image coding multiplexer.
In addition, an information indication f for the activation or, respectively, deactivation of the loop filter LF is provided.
After transmission of the image information via the transmission medium xc3x9cM, the decoding of the transmitted data can take place in the second computer R2. For this purpose, in the second computer R2 an image decoding unit is provided that has for example the design of the reconstruction loop of the arrangement shown in FIG. 2.
In object-based image coding methods, each image object is first decomposed into blocks of a fixed size, e.g. likewise 8xc3x978 image points. After this decomposition, a part of the resulting image blocks is located completely inside an image object BO. This situation is shown in FIG. 4. The image B contains at least one image object BO that is outlined with an object edge OK of the image object BO. In addition, image blocks BB with 8xc3x978 image points BP are shown. Image blocks BB that contain at least a part of the object edge OK are called edge image blocks RBB in the following.
Image blocks BB that are located completely inside the image object BO after the decomposition can be coded with a standard block-based discrete cosine transformation, using the above-named block-based image coding method. However, the edge image blocks RBB are partly filled with image information, and must be coded using a separate method.
For the coding of the edge image blocks RBB, up to now there have been two basic approaches.
From a first document, ISO/IEC JTC1/SC29/WG11, MPEG4 Video Verification Model-Version 5.0, Doc. N1469, November 1996, pp. 55-59, it is known to supplement the image information of the image object BO within the edge image block RBB by means of a suitable extrapolation method of the coding information onto the surface of the complete edge image block RBB. This procedure is called padding. The supplemented surface is subsequently coded with a standard 2-dimensional discrete cosine transformation.
Alternatively the first document and a second document, T. Sikora and B. Makai, Shape Adaptive DCT for Generic Coding of Video, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 5, pp. 59-62, February 1995, it is known that the given image object BO is transformed separately according to lines and columns. This procedure is called shape-adapted transformation coding; in the concrete case of the application of a DCT, it is called shape-adapted DCT. The DCT coefficients allocated to the image object BO are determined in such a way that the image points BP of an edge image block RBB that do not belong to the image object BO are screened out. A transformation is then applied, line-by-line at first, to the remaining image points BP, whose length corresponds to the number of remaining image points in this line. The resulting coefficients are oriented horizontally and are subsequently subjected to a further one-dimensional DCT in the vertical direction, with corresponding length. The same method is hereby used both for the intra-image coding and for the inter-image coding.
The known method of shape-adaptive transformation coding specified above has, above all, the disadvantage that only a relatively poor compression factor of the image data to be compressed is achieved.
The known rule for coding prediction error images in shape-adapted transformation coding is based on a transformation matrix DCTxe2x88x92N with the following construction:
DCTxe2x88x92N(p, kO)=xcex3xc2x7cos(pxc2x7(k+xc2xd)xc2x7Π/N)k,p=0xe2x86x92Nxe2x88x92xe2x80x83xe2x80x83(1).
The value is hereby xcex3=1/2 for the case p=0, and is xcex3=1 for all other cases.
N designates a size of the image vector to be transformed within which the transformed image points are contained.
DCTxe2x88x92N designates a transformation matrix of size Nxc3x97N.
With p, k, indices are designated with p, k xcex5(0, Nxe2x88x921).
According to the known procedure, the shape-adapted PCT of an image segment is determined in that first each column of the segment is vertically transformed according to the rule
xe2x80x83cj=2xc2x7(2/N)xc2x7DCTxe2x88x92Nxc2x7xjxe2x80x83xe2x80x83(2)
and subsequently the same rule (2) is applied to the resulting data in the horizontal direction. The rule according to equation (2) is however not optimal for the coding of prediction error images.
From a third document, A. K. Jain, Image Data Compression: A Review, Proceedings of the IEEE, Vol. 69, No.3, pp. 349-389, March 1981, foundations of block-based image coding are known.
The invention is thus based on the problem of indicating methods for image coding and for image decoding and arrangements for image coding and for image decoding with which a shape-adapted transformation coding is achieved with an improved compression factor for the image data.
In the method according to present invention for the coding of a digitized image, the image coding takes place in an intra-image coding mode or in an inter-image coding mode. In the intra-image coding mode, the image information of the image points is transformed, and in the inter-image coding mode, difference image information of image information of two successive images is transformed. In the inter-image coding mode, a first shape-adapted transformation coding is carried out, and in the intra-image coding mode a second shape-adapted transformation coding, different from the first shape-adapted transformation coding, is carried out.
A particular advantage of this procedure is that the use of two different transformation codings makes it possible to distribute uniformly over all image points Bp the quantization error in the subsequent quantization of the spectral coefficients resulting from the transformation, and the quantization error has the same mean value as in the case of a normal 8xc3x978 image block.
This method is suitable above all for the coding of edge image blocks of an image segment.
Overall, the method enables a significantly improved coding efficiency, i.e., at the same data rate the image quality that can be achieved increases. As specified below, in contrast to the known procedure, the use of the same transformation in intra-image coding and in inter-image coding given a shape-adapted image coding, a considerably improved signal/noise ratio of approximately one dB can be achieved without additional computing expense.
In the method according to a further embodiment, in the decoding in the intra-image coding mode a first inverse shape-adapted transformation coding is carried out. In the intra-image coding mode, a second inverse shape-adapted transformation coding is carried out. The first inverse shape-adapted transformation coding and the second inverse shape-adapted transformation coding are different.
This method likewise comprises the advantages shown correspondingly above for the image coding.
In the arrangement according to present invention for the execution of the method, a transformation coding unit is provided for the shape-adapted transformation coding of the image points and/or a transformation decoding unit is provided for the inverse shape-adapted transformation coding. The transformation coding unit or, respectively, the transformation decoding unit is constructed in such a way that in the intra-image coding mode a first shape-adapted transformation coding or, respectively, a first inverse shape-adapted transformation coding is carried out. In the inter-image coding mode, a second shape-adapted transformation coding or, respectively, a second inverse shape-adapted transformation coding is carried out. The first shape-adapted transformation coding or, respectively, the first inverse shape-adapted transformation coding and the second shape-adapted transformation coding or, respectively, the second inverse shape-adapted transformation coding are different.
The advantages specified above also hold for the arrangement.
In a development of the invention, it is advantageous that at least one of the shape-adapted transformation codings or, respectively, at least one of the inverse shape-adapted transformation codings take place in such a way that the signal energy of the image points to be transformed in the spatial domain is approximately equal to the signal energy of the transformed image points in the frequency domain.
In other words, this means that the corresponding shape-adapted transformation coding or, respectively, inverse shape-adapted transformation coding is orthonormalized. A particular advantage of this procedure is that the quantization error in the subsequent quantization of the spectral coefficients resulting due to the transformation is distributed uniformly over all image points, and the quantization error has the same mean value as in the case of a normal 8xc3x978 image block.
In a development of the method for image coding, it is in addition advantageous to form the transformation coefficients cj of the image points xj to be transformed according to the following rule:
xe2x80x83cj=((2/N))xc2x7DCTxe2x88x92N(p,k)xc2x7xjxe2x80x83xe2x80x83(3),
whereby
N designates a size of the image vector to be transformed in which the transformed image points are contained,
DCTxe2x88x92N designates a transformation matrix of size Nxc3x97N,
p, k designate indices, with p, k xcex5(0, Nxe2x88x921).
As can be seen in the rule (3), the considerable improvement is achieved solely by means of a scaling of the transformation rule that is different from the known procedure.
The above-specified developments for the method for image coding are likewise provided as developments for image decoding, with the rule for inverse transformation coding with the correspondingly inverse rule.
The developments of the method are likewise advantageous for constructions of the transformation coding unit of the arrangement for image coding.
These methods are suited above all for the coding or, respectively, decoding of edge image blocks of an image segment.